Network Pharmacology Reveals Curcuma aeruginosa Roxb. Regulates MAPK and HIF-1 Pathways to Treat Androgenetic Alopecia

Simple Summary Androgenetic alopecia (AGA) represents the most common form of hair loss experienced by both men and women. Curcuma aeruginosa Roxb., a plant known for its medicinal properties, has shown promise in reversing this hair loss disorder for its hair growth effects and anti-androgenic effects. Despite its promising potential, the mechanism of action by which it acts remains unknown. As such, this study unveiled how this plant works against hair loss by identifying its bioactive compounds, the gene its targets, and the potential mechanism involved in the therapy of AGA using network pharmacology and molecular docking. The findings revealed insights into how C. aeruginosa can potentially prevent AGA, highlighting its potential for developing new, safe therapies for AGA, benefiting those affected by this condition. Abstract Androgenetic alopecia (AGA) is the most prevalent hair loss disorder worldwide, driven by excessive sensitivity or response to androgen. Herbal extracts, such as Curcuma aeruginosa Roxb., have shown promise in AGA treatment due to their anti-androgenic activities and hair growth effects. However, the precise mechanism of action remains unclear. Hence, this study aims to elucidate the active compounds, putative targets, and underlying mechanisms of C. aeruginosa for the therapy of AGA using network pharmacology and molecular docking. This study identified 66 bioactive compounds from C. aeruginosa, targeting 59 proteins associated with AGA. Eight hub genes were identified from the protein–protein interaction network, namely, CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3. Topological analysis of components–targets network revealed trans-verbenol, myrtenal, carvone, alpha-atlantone, and isoaromandendrene epoxide as the core components with potential significance in AGA treatment. The molecular docking verified the binding affinity between the hub genes and core compounds. Moreover, the enrichment analyses showed that C. aeruginosa is involved in hormone response and participates in HIF-1 and MAPK pathways to treat AGA. Overall, this study contributes to understanding the potential anti-AGA mechanism of C. aeruginosa by highlighting its multi-component interactions with several targets involved in AGA pathogenesis.


Introduction
Androgenic alopecia (AGA) is the most prevalent hair loss disorder, causing at least 95% of all pattern hair loss cases, such as hair thinning among women and baldness in men [1].AGA, an androgen-dependent alopecia with genetic origin, features progressive replacement of thick, long terminal hair with fine, small vellus hair.The androgens responsible for AGA are testosterone and its biologically active metabolite, dihydrotestosterone Biology 2024, 13, 497 2 of 22 (DHT).High levels of, or hypersensitivity to, DHT miniaturizes hair follicles, causing a shortened anagen phase of the hair growth cycle and, eventually, hair loss.
Although AGA does not pose a significant health risk, it may affect an individual's mental and social well-being, amplifying the need for treatment [2].Currently, only two drugs are approved by the Food and Drug Administration (FDA) to treat AGA, namely, oral finasteride and topical minoxidil.Although they exhibited favorable efficacy, side effects are reported, such as sexual dysfunction from finasteride [3] and dermatitis from minoxidil [4].Because of this, many opt for complementary and alternative medicine (CAM) interventions.One of these is the use of herbal extracts, which have been shown to stop hair loss and encourage hair growth [5].
Curcuma aeruginosa Roxb. is a rhizomatous plant rich in ethnomedicinal values for treating several ailments, exhibiting a wide spectrum of pharmacologic activities such as antioxidant [6], anti-cancer [7], antimicrobial [8], anti-HIV-1 [9], uterine-relaxant [10], and anti-androgenic effects.Phytochemically, C. aeruginosa is a rich source of sesquiterpenes, which have been shown to exhibit anti-androgenic action in vitro and in vivo by suppressing the growth of testosterone-induced human prostate cancer cells and androgendependent hamster flank gland model, respectively [11].Additionally, clinical trials have demonstrated that C. aeruginosa is a promising, efficient component of AGA hair tonic for slowing hair loss and stimulating hair growth [12,13].Despite exhibiting therapeutic effects on AGA, the mechanism by which C. aeruginosa acts remains unknown.
Therefore, the purpose of this study is to elucidate the potential mechanism of C. aeruginosa against AGA through network pharmacology and molecular docking.Network pharmacology has become a commonly used tool in drug research to unveil how drugs interact with their targets, pathways, and associated disorders [14].Meanwhile, molecular docking is utilized to confirm the potential associations of compounds and target genes predicted in the network pharmacological analysis [15].
This study is limited to investigating the influence of C. aeruginosa on AGA using an in silico approach, as none had been reported.Initially, the bioactive compounds of the said plant were screened out and selected.The overlap between its predicted targets and AGA-linked target genes was acquired for protein-protein interaction (PPI) construction and GO and KEGG enrichment analyses.Furthermore, the components-targets-pathways network was visualized to give a general overview of the molecular mechanisms of C. aeruginosa against AGA.Finally, molecular docking was employed to verify the affinity between the components and targets.

Screening of Bioactive Compounds in C. aeruginosa
The Indian Medicinal Plants, Phytochemistry and Therapeutics 2.0 (IMPPAT 2.0) online database (https://cb.imsc.res.in/imppat/home(accessed on 31 January 2024) [16] was used in search of compounds present in C. aeruginosa.This database integrates the phytochemicals of Indian medicinal plants and their pharmacokinetic properties, including drug-likeness, blood-brain barrier permeation, gastrointestinal absorption, etc. Literature mining was also conducted for further collection.The physicochemical, drug-like, and pharmacokinetic parameters of the additional compounds were computed through Swis-sADME (http://www.swissadme.ch/(accessed on 1 February 2024)) [17].The compounds that met at least three drug-likeness principles and had high gastrointestinal absorption and an oral bioavailability greater than 30% were selected and classified as bioactive ones.

Target Gene Prediction in C. aeruginosa
The targets of the screened potentially bioactive compounds were determined through SwissTargetPrediction (http://www.swisstargetprediction.ch/ (accessed on 30 May 2024) [18], a web server that uses a combination of two-dimensional and threedimensional similarity metrics with known ligands to reliably predict the protein targets of compounds.For the target genes prediction C. aeruginosa, the canonical SMILES of compounds were copied to SwissTargetPrediction."Homo sapiens" was selected as the study species to restrict the analysis of the target genes to those within humans, ensuring the relevance to human biology.

Protein-Protein Interaction Network
The target genes for the protein-protein interaction (PPI) network were obtained by determining the common targets of C. aeruginosa and AGA through a Venn diagram plotted in Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/accessed on 30 May 2024).The PPI network of common targets was constructed by the Search Tool for Retrieval of Interacting Genes (STRING) (https://string-db.org/accessed on 30 May 2024) [23], a database of predicted and known protein interactions, to investigate the relationship between the imported genes.The analysis was restricted to proteins found in "Homo sapiens" species.Afterward, the PPI network was imported into the Cytoscape (version 3.10.0)software for further analysis.CytoHubba, a Cytoscape plugin, was used to identify the potential hub target genes in the network.Three algorithms were employed-maximal clique centrality (MCC), maximum neighborhood component (MNC), and degree-to rank the best 10 genes based on the scores.The results were then intersected in which the overlapped genes represent the final set of hub targets.Moreover, MCODE was used for the cluster analysis of the PPI network with parameters set to default.

Gene Ontology and Pathway Enrichment Analysis
The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed to explore the biological mechanism underlying C. aeruginosa and its influence on AGA.GO is widely recognized for defining and describing genes from three aspects-biological process (BP), molecular function (MF), and cellular component (CC).KEGG, on the other hand, is a massive compilation of databases on drugs, genomes, enzymes, and biological pathways, among others.The enrichment analysis for the common targets was conducted using Metascape (https://metascape.org/gp/index.htmlaccessed on 30 May 2024) [24], a gene annotation and analysis repository.Herein, the analysis was considered for "Homo sapiens" only, and p-value < 0.01 served as the cutoff.The results were taken as the top 20 based on descending −log10(p-value).The results were visualized in the form of a bar chart with the help of the Scientific and Research plot tool (SRplot) (http://www.bioinformatics.com.cn/SRplotaccessed on 30 May 2024).

Components-Targets-Pathways Network Construction
Cytoscape (version 3.10.0)was used to plot a network for the top 20 KEGG pathways with the corresponding potentially bioactive compounds and targets associated with them to effectively display the interactions between C. aeruginosa and AGA and ultimately characterize the therapeutic mechanisms of the former on the latter.

Molecular Docking
Molecular docking was applied to validate the binding between the core compounds of C. aeruginosa and the identified hub target genes.The crystal structures of human hub genes were downloaded from the RCSB Protein Data Bank (PDB) (https://www.rcsb.org/accessed on 30 May 2024), while the 3D structures of the C. aeruginosa core compounds were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/accessed on 30 May 2024).The docking was performed using CB-Dock 2 (http://clab.labshare.co.uk/cb-dock/php/index.php accessed on 30 May 2024) [25], a protein-ligand blind docking tool that integrates the well-known molecular docking software Autodock Vina 1.1.2to identify the binding site and predict binding pose.

Bioactive Compounds in C. aeruginosa
Through IMPPAT, 93 compounds were found in the C. aeruginosa plant.Additionally, a literature search reveals a review article that described the phytochemical composition of C. aeruginosa [26], extracting 10 more compounds after eliminating the duplicates and those lacking structural information.In total, 103 compounds were screened, as shown in Table 1.However, only 66 were found to be bioactive after filtering with the parameters of an oral bioavailability greater than 30%, high gastrointestinal absorption, and adherence to three druglike rule-based filters, with one being the Lipinski rules.Interestingly, all compounds had bioavailability scores of 0.55, besides their high gastrointestinal absorption.A bioavailability score greater than 0.55 is assigned to any compound complying with Lipinski's rules and is considered ideal as it indicates the compound's optimal absorption [27].

Predicted Target Genes of C. aeruginosa and AGA
The 66 druglike compounds of C. aeruginosa had their target genes predicted through SwissTargetPrediction, yielding 795 human proteins after removing the duplicates (Supplementary Table S1).On the other hand, a total of 672 genes related to AGA were collected, of which 100 genes were from GenClip, 112 from DisGeNet, 452 from GeneCard, and 8 from OMIM.After the deletion of duplicates, 562 potential AGA-related targets were obtained (Supplementary Table S2).

Common Targets of C. aeruginosa and AGA
The intersection of potential C. aeruginosa target genes and AGA-related genes revealed 59 overlapping genes, as presented by the Venn diagram shown in Figure 1.The overlapped genes, as listed in Table A1

Protein-Protein Interaction (PPI) Network
The 59 targets associated with AGA and determined as targets for C. aeruginosa bioactive compounds were imported to STRING to construct a PPI network and analyze the relationship between them.An original PPI network comprising 59 nodes, of which one

Protein-Protein Interaction (PPI) Network
The 59 targets associated with AGA and determined as targets for C. aeruginosa bioactive compounds were imported to STRING to construct a PPI network and analyze the relationship between them.An original PPI network comprising 59 nodes, of which one was disconnected, and 449 edges with an average node degree of 15.2 were produced, as shown in Figure 2. Also, it had an average local clustering coefficient of 0.629, indicating how connected the nodes were.The expected number of edges was 178, which was much lesser than the actual edges of the network, and the PPI enrichment p-value was observed to be <1.0 × 10 −16 .Hence, the network had significantly greater interactions than expected for the random network of similar size, and the proteins, represented by nodes, were at least partially biologically connected as a cluster.Subsequently, the original PPI network from STRING was reconstructed in Cytoscape for visualization and further analysis.The reconstructed network, as shown in Figure 3, contained 58 nodes and 449 edges while removing one unconnected gene.The color of the node differed depending on its degree value, with darker colors reflecting greater values.The larger the degree, the more the involvement of biological functions, suggesting protein's vital role in the network.Thus, the nodes with darker colors may serve as essential targets for the therapeutic effects of C. aeruginosa in AGA.Subsequently, the original PPI network from STRING was reconstructed in Cytoscape for visualization and further analysis.The reconstructed network, as shown in Figure 3, contained 58 nodes and 449 edges while removing one unconnected gene.The color of the node differed depending on its degree value, with darker colors reflecting greater values.The larger the degree, the more the involvement of biological functions, suggesting protein's vital role in the network.Thus, the nodes with darker colors may serve as essential targets for the therapeutic effects of C. aeruginosa in AGA.

Identification of Hub Genes
To determine the hub targets, the CytoHubba plug-in of Cytoscape 3.

Identification of Hub Genes
To determine the hub targets, the CytoHubba plug-in of Cytoscape 3.10.2was used to analyze each node by incorporating three topological algorithms, namely, maximal clique centrality (MCC), maximum neighborhood component (MNC), and degree.Figure 4 shows the top 10 genes predicted by each algorithm based on their scores.Eight genes (CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3) were screened out after intersecting the three results, as revealed in Figure 4D.These highly connected genes, as shown in Figure 4E, represent the hub target genes of C. aeruginosa in AGA treatment.

Cluster Analysis of PPI Network
MCODE plug-in was employed for cluster analysis of the PPI, yielding three cluster modules, as shown in Figure 5. Module 1 possessed 23 nodes and 186 edges; Module 2 comprised 6 nodes and 11 edges; and Module 3 comprised 3 nodes and 3 edges.Module 1 had the highest average score of 16.91, followed by Module 2 and Module 3, whose scores were 4.40 and 3.00, respectively.In the PPI network, modules with greater average scores may have more significant roles.Hence, Module 1 was the most important.Consequently, all identified hub genes were clustered in this module.to analyze each node by incorporating three topological algorithms, namely, maximal clique centrality (MCC), maximum neighborhood component (MNC), and degree.Figure 4 shows the top 10 genes predicted by each algorithm based on their scores.Eight genes (CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3) were screened out after intersecting the three results, as revealed in Figure 4D.These highly connected genes, as shown in Figure 4E, represent the hub target genes of C. aeruginosa in AGA treatment.

Cluster Analysis of PPI Network
MCODE plug-in was employed for cluster analysis of the PPI, yielding three cluster modules, as shown in Figure 5. Module 1 possessed 23 nodes and 186 edges; Module 2 comprised 6 nodes and 11 edges; and Module 3 comprised 3 nodes and 3 edges.Module 1 had the highest average score of 16.91, followed by Module 2 and Module 3, whose scores were 4.40 and 3.00, respectively.In the PPI network, modules with greater average scores may have more significant roles.Hence, Module 1 was the most important.Consequently, all identified hub genes were clustered in this module.

GO and KEGG Enrichment Analyses
GO and KEGG enrichment analyses of the 59 common targets in Metascape yielded 1055 biological processes, 64 molecular functions, 36 cellular components, and 150 KEGG pathway terms, wherein the top 20 terms in each category are visualized in Figure 6 and listed in Tables A2-A5 (see Appendix A).Based on biological processes, the function of the bioactive compounds is mostly concentrated on response to peptides, lipids, and hormones, among others, suggesting that C. aeruginosa can modulate the hormones participating in AGA.Additionally, the majority of the genes are coded for protein in the receptor complex, transcription regulator complex, and plasma membrane protein complex, suggesting that C. aeruginosa targets protein complexes.Also, the cellular components included the cell body, which may indicate the potential interactions of C. aeruginosa bioactive compounds with cells relevant to the hair growth cycle.Molecularly, the functions of C. aeruginosa were mainly enriched in the activity of and binding to protein kinase and transcription factors, as well as hormone binding and nuclear receptor activity.This indicated that C. aeruginosa affects these proteins, which are the categories of the identified

GO and KEGG Enrichment Analyses
GO and KEGG enrichment analyses of the 59 common targets in Metascape yielded 1055 biological processes, 64 molecular functions, 36 cellular components, and 150 KEGG pathway terms, wherein the top 20 terms in each category are visualized in Figure 6 and listed in Tables A2-A4 (see Appendix A).Based on biological processes, the function of the bioactive compounds is mostly concentrated on response to peptides, lipids, and hormones, among others, suggesting that C. aeruginosa can modulate the hormones participating in AGA.Additionally, the majority of the genes are coded for protein in the receptor complex, transcription regulator complex, and plasma membrane protein complex, suggesting that C. aeruginosa targets protein complexes.Also, the cellular components included the cell body, which may indicate the potential interactions of C. aeruginosa bioactive compounds with cells relevant to the hair growth cycle.Molecularly, the functions of C. aeruginosa were mainly enriched in the activity of and binding to protein kinase and transcription factors, as well as hormone binding and nuclear receptor activity.This indicated that C. aeruginosa affects these proteins, which are the categories of the identified AGA-related targets of C. aeruginosa.Lastly, The KEGG enrichment showed the potential signaling pathways by which C. aeruginosa played an anti-AGA role, including MAPK and HIF-1 signaling pathways.

Components-Targets-Pathways Network
A network representation of the interaction between C. aeruginosa bioactive compounds, its potential target genes linked to AGA, and pathways associated with the targets was constructed through Cytoscape and portrayed as the components-targets-pathways network shown in Figure 7.The compounds, targets, and pathways were represented by yellow elliptical nodes, blue round rectangular nodes, and red arrow-shaped nodes, respectively.The network contained 144 nodes (66 compounds, 58 target genes, and 20 pathways) and 847 edges, showing the intricate relationships between them.Topological analysis of the components-targets network revealed trans-verbenol, myrtenal, carvone, alpha-atlantone, and isoaromandendrene epoxide as core components, exhibiting degrees of 16, 15, 15, 14, and 14, respectively, which were the highest among the compounds.Generally, this network revealed the multi-components of C. aeruginosa exerting synergistic multi-targeted effects against AGA.

Components-Targets-Pathways Network
A network representation of the interaction between C. aeruginosa bioactive compounds, its potential target genes linked to AGA, and pathways associated with the targets was constructed through Cytoscape and portrayed as the components-targets-pathways network shown in Figure 7.The compounds, targets, and pathways were represented by yellow elliptical nodes, blue round rectangular nodes, and red arrow-shaped nodes, respectively.The network contained 144 nodes (66 compounds, 58 target genes, and 20 pathways) and 847 edges, showing the intricate relationships between them.Topological analysis of the components-targets network revealed trans-verbenol, myrtenal, carvone, alpha-atlantone, and isoaromandendrene epoxide as core components, exhibiting degrees of 16, 15, 15, 14, and 14, respectively, which were the highest among the compounds.Generally, this network revealed the multi-components of C. aeruginosa exerting synergistic multi-targeted effects against AGA.

Molecular Docking
The hub target genes (CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3) were molecularly docked with the core components to ascertain whether the core components (trans-verbenol, myrtenal, carvone, alpha-atlantone, and isoaromandendrene epoxide) of C. aeruginosa could bind to the protein targets predicted by SwissTargetPrediction.Two positive controls were also docked, namely, finasteride and minoxidil.Generally, the binding energy between the ligand compounds and receptor proteins dictates their structural stability.The lower the binding energy, the greater the affinity between the protein target and component.Based on the molecular docking studies, as shown in Figure 8, the binding energy between the core compounds and hub genes ranged from −4.6 to −8.9 kcal/mol.The results showed that the binding energies were less than 0, suggesting they spontaneously bound to one another.Binding energies less than −5 kcal/mol are believed to create more stable structures as opposed to those with greater binding energies.Hence, all molecules could bind stably to the target genes with strong affinity except for carvone and myrtenal when bound to HIF1A.AKT1 and AR, among the target genes, had the

Molecular Docking
The hub target genes (CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3) were molecularly docked with the core components to ascertain whether the core components (trans-verbenol, myrtenal, carvone, alpha-atlantone, and isoaromandendrene epoxide) of C. aeruginosa could bind to the protein targets predicted by SwissTargetPrediction.Two positive controls were also docked, namely, finasteride and minoxidil.Generally, the binding energy between the ligand compounds and receptor proteins dictates their structural stability.The lower the binding energy, the greater the affinity between the protein target and component.Based on the molecular docking studies, as shown in Figure 8, the binding energy between the core compounds and hub genes ranged from −4.6 to −8.9 kcal/mol.The results showed that the binding energies were less than 0, suggesting they spontaneously bound to one another.Binding energies less than −5 kcal/mol are believed to create more stable structures as opposed to those with greater binding energies.Hence, all molecules could bind stably to the target genes with strong affinity except for carvone and myrtenal when bound to HIF1A.AKT1 and AR, among the target genes, had the highest binding affinity with the core compounds.This may imply that targeting these proteins plays an essential role in AGA treatment by C. aeruginosa bioactive compounds.Strikingly, alpha-atlantone and isoaromandendrene epoxide demonstrated superior affinity to AR when compared to controls.The top four stable ligand-receptor complexes were selected for visualization, as shown in Figure 9, and their binding sites were tabulated in Table 2. Since both alpha-atlantone and isoaromandendrene epoxide are sesquiterpenes, they are bound to similar amino acid residue sites in the AKT1 complex.
Biology 2024, 13, x FOR PEER REVIEW 13 of 24 highest binding affinity with the core compounds.This may imply that targeting these proteins plays an essential role in AGA treatment by C. aeruginosa bioactive compounds.Strikingly, alpha-atlantone and isoaromandendrene epoxide demonstrated superior affinity to AR when compared to controls.The top four stable ligand-receptor complexes were selected for visualization, as shown in Figure 9, and their binding sites were tabulated in Table 2. Since both alpha-atlantone and isoaromandendrene epoxide are sesquiterpenes, they are bound to similar amino acid residue sites in the AKT1 complex.The bluer the color, the greater the binding energy and binding affinity between the ligand and the receptor.
Biology 2024, 13, x FOR PEER REVIEW 13 of 24 highest binding affinity with the core compounds.This may imply that targeting these proteins plays an essential role in AGA treatment by C. aeruginosa bioactive compounds.Strikingly, alpha-atlantone and isoaromandendrene epoxide demonstrated superior affinity to AR when compared to controls.The top four stable ligand-receptor complexes were selected for visualization, as shown in Figure 9, and their binding sites were tabulated in Table 2. Since both alpha-atlantone and isoaromandendrene epoxide are sesquiterpenes, they are bound to similar amino acid residue sites in the AKT1 complex.

Discussion
AGA is a multifactorial hair loss disorder, and those suffering from this disease have limited options for medical treatment.Drugs like finasteride and minoxidil cause side effects, restricting their long-term administration.Moreover, invasive treatments like hair transplantation and platelet-rich plasma (PRP) require repeated procedures, resulting in costly investments [28,29].Currently, topical herbal preparations are becoming more commonly available due to their greater compliance rate, broader active spectrum, more affordable price, and lesser side effects [30,31].Thus, they are anticipated to be extensively utilized for AGA complementary and alternative medicine.C. aeruginosa, as a topical preparation, has been shown to exhibit anti-androgenic and hair growth effects due to its phytochemical content that may target different pathways involved in AGA.Accordingly, network pharmacology fits as a valid method for elucidating its multicomponent-multitarget anti-AGA mechanism.
The network pharmacology results revealed five compounds-trans-verbenol, myrtenal, carvone, alpha-atlantone, and isoaromandendrene epoxide-that might be the core components in C. aeruginosa and enable it to induce therapeutic effects against AGA.However, no studies reported their anti-androgenic and trichogenic effects yet, recommending further in vivo and in vitro studies to test their anti-AGA potential.Molecular docking analysis confirmed that the core components bound with the eight hub genes-CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3-implying potential interactions and modulation of these genes to treat AGA.
CASP3, whose role is central in executing cell apoptosis, is overexpressed in the bald area of AGA patients in the early courses of the disease, revealing the presence of inflammation and apoptosis at such stages [32].Activation of CASP3 inhibits the PI3K/AKT signaling pathway, which mediates extracellular signals and intracellular responses and is critically involved in the regulation of cell proliferation, growth, and differentiation.This, in turn, stops hair follicles from transitioning from the resting phase to the anagen phase, blocks cell proliferation, promotes apoptosis, and finally degenerates hair follicles [33].As such, inhibiting CASP3 activation helps reverse hair follicles' entry to the abnormal and degenerative anagen phases and stimulates hair growth.
Likewise, AKT1, one of the relevant serine/threonine protein kinases, regulates cell apoptosis and proliferation and serves as the main downstream molecule of the PI3K/AKT pathway, whose role is necessary for de novo hair follicle regeneration [34].In response to extracellular signals, AKT1 can either act as a positive or negative regulator of the PI3K/AKT pathway via PIK3, leading to AR expression regulation [35].
Contrary to the alopecia-inducing effects of the earlier hub genes, STAT3, HIF1A, and MAPK3 are reported to counteract hair loss.STAT3 is required in the hair cycle during the onset of anagen because it activates keratinocytes for the continuation of the hair cycle [46].Loss of STAT3 functions in keratinocytes increases apoptotic hair follicle stem cells (HFSCs), impairing the hair cycle process [47].Contrastingly, gain of function raises progenitor cells and HFSCs above the bulge region, ensuring proper maintenance and growth of hair follicles [48].With this, STAT3 regulation is critical in maintaining hair cycling and growth.Meanwhile, HIF1A regulates trichogenic gene expression in DPCs [49], suggesting a similar function to minoxidil, which exerts trichogenic effects ascribed by its vasodilating properties [50].Lastly, MAPK's role in regenerating HFSCs, inducing anagen hair cycle, and modulating root hair tip growth is important in hair growth stimulation [51,52].Specifically, when MAPK3 was upregulated, hair growth improved [53].
The GO enrichment analysis suggested that C. aeruginosa may regulate hormones, such as androgen, estrogen, and cortisol.Androgens, like testosterone and DHT, activate AR signaling, upregulating genes involved in hair growth suppression resulting from growth inhibition factors, vascular regression around dermal papilla [54], apoptosis [55], and DPC aging [56].On the other hand, estrogen maintains hair follicle cycling [57], encourages healthy hair growth by activating the Wnt/β-catenin signaling pathway to sustain HFSC differentiation and proliferation [58,59], and shields hair follicles from oxidative stress and eventually hair follicle aging by modulating antioxidant enzymes [60].Lastly, corticosterone, the cortisol counterpart in mice and the main stress hormone, disallows the entry of HFSCs into the anagen phase [61].Thus, chronic stress can quicken hair aging and loss by influencing HFSC.
On the other hand, the KEGG enrichment showed the potential signaling pathways by which C. aeruginosa played an anti-AGA role, including MAPK and HIF-1 signaling pathways.The identified hub genes were implicated in the MAPK pathway (AKT1, CASP3, and MAPK3) and the HIF-1 pathway (AKT1, GIF1A, IL6, MAPK3, and STAT3) through which core compounds may act to modulate them.The combined effects of the compounds through their regulation of MAPK and HIF-1 pathways, together with direct interaction with other hub genes, create a synergistic approach to address various aspects of AGA pathogenesis.MAPK pathway is important in regulating normal cell survival, migration, proliferation, and migration [62].In hair, MAPK has been revealed to amplify growth factor production [63], regulate the hair cycle and quiescence of HFSC [51], and promote HFSC differentiation and proliferation [64], thereby influencing hair follicle morphogenesis and regeneration.Currently, four MAPK signal transduction pathways are known in mammalian cells: extracellular signal-regulated kinases (ERKs) which stimulate DPC proliferation and anagen phase [65,66]; and p38 MAPKs and Jun N-terminal kinases (JNKs), both of which control Wnt/β-catenin pathway [67,68], the master regulator of hair cells.
Whereas the HIF-1 pathway has been shown to govern hair regeneration, regulating the size and shape of dermal papilla [69,70].AGA has been associated with insufficient nutrient supply and reduced blood vessels.Consequently, HIF stimulation can come into play in this by regulating neovascularization and regeneration as DPCs react to hypoxia [71].The HIF-1 pathway is strongly linked to the mechanism of action of minoxidil attributed to its vasodilating properties [72].Clinical trials showed that the combination of minoxidil and C. aeruginosa stimulated hair growth more effectively than minoxidil alone [12,13].The topical application of C. aeruginosa complimented minoxidil as it increased hair growth and decreased hair shedding by enhancing penetration [12,13].This may be caused by C. aeruginosa's potential regulation of the HIF-1 pathway, which is said to increase vasodilation, promoting conducive conditions for hair growth.Figure 10 shows the potential mechanism of C. aeruginosa against AGA.It is essential to consider that although MAPK and HIF-1 pathways influence AGA, their roles are part of a complex cascade of events rather than a direct one.
OR PEER REVIEW 16 of 24 [12,13].The topical application of C. aeruginosa complimented minoxidil as it increased hair growth and decreased hair shedding by enhancing penetration [12,13].This may be caused by C. aeruginosa's potential regulation of the HIF-1 pathway, which is said to increase vasodilation, promoting conducive conditions for hair growth.Figure 10 shows the potential mechanism of C. aeruginosa against AGA.It is essential to consider that although MAPK and HIF-1 pathways influence AGA, their roles are part of a complex cascade of events rather than a direct one.Notably, Module 3 derived from the cluster analysis of the PPI network contained SRD5A2, SRD5A1, and CYP17A1, which are involved in androgen biosynthesis.SRD5As amplify DHT production in hair follicles of the scalp, causing AGA [73].To date, steroidal drugs finasteride and dutasteride are used to treat AGA by acting as SRD5A inhibitors.Finasteride selectively inhibits SRD5A2 while dutasteride inhibits both SRD5A1 and SRD5A2.Accordingly, a prior study suggested that the potential mechanism of C. aeruginosa for its anti-androgenic effect is SRD5A inhibition [11].Its sesquiterpene content, specifically germacrone, was on par with finasteride when it came to exhibiting anti-androgenic activity.It inhibited SRD5A to a similar extent as finasteride in suppressing the growth of testosterone-induced growth of human prostate cancer cells (in vitro) and hamster flank gland model (in vivo), thereby suggesting C. aeruginosa as a novel SRD5A inhibitor.Similarly, CYP17A1 is needed in DHT production, both in anterior and posterior routes [74,75].Minoxidil suppresses CYP17A1 to inhibit AGA [76].Therefore, synergizing this with MAPK and HIF-1 pathways may influence both anti-androgenic activities and hair growth effects, promoting healthy hair follicles and eventually preventing AGA.
While AGA affects both men and women, men are more commonly and severely impacted because of innate higher levels of androgens.Although C. aeruginosa exhibited trichogenic activities that could impact women too, men with genetic predispositions to AGA are likely to see more significant benefits from C. aeruginosagiven its anti-androgenic effects.Additionally, younger men, whose AGA symptoms are not yet more pronounced, may experience greater advantages from early intervention using it to potentially prevent AGA.Further research is recommended to fully comprehend these effects across different patient populations.In terms of safety, no side effects were reported on the topical application of C. aeruginosa in clinical trials [12,13], as opposed to those associated with finasteride and minoxidil, namely, sexual dysfunction and dermatological problems.This underscores the potential of C. aeruginosa as an AGA treatment, warranting further investigation.Notably, Module 3 derived from the cluster analysis of the PPI network contained SRD5A2, SRD5A1, and CYP17A1, which are involved in androgen biosynthesis.SRD5As amplify DHT production in hair follicles of the scalp, causing AGA [73].To date, steroidal drugs finasteride and dutasteride are used to treat AGA by acting as SRD5A inhibitors.Finasteride selectively inhibits SRD5A2 while dutasteride inhibits both SRD5A1 and SRD5A2.Accordingly, a prior study suggested that the potential mechanism of C. aeruginosa for its anti-androgenic effect is SRD5A inhibition [11].Its sesquiterpene content, specifically germacrone, was on par with finasteride when it came to exhibiting anti-androgenic activity.It inhibited SRD5A to a similar extent as finasteride in suppressing the growth of testosteroneinduced growth of human prostate cancer cells (in vitro) and hamster flank gland model (in vivo), thereby suggesting C. aeruginosa as a novel SRD5A inhibitor.Similarly, CYP17A1 is needed in DHT production, both in anterior and posterior routes [74,75].Minoxidil suppresses CYP17A1 to inhibit AGA [76].Therefore, synergizing this with MAPK and HIF-1 pathways may influence both anti-androgenic activities and hair growth effects, promoting healthy hair follicles and eventually preventing AGA.
While AGA affects both men and women, men are more commonly and severely impacted because of innate higher levels of androgens.Although C. aeruginosa exhibited trichogenic activities that could impact women too, men with genetic predispositions to AGA are likely to see more significant benefits from C. aeruginosa given its anti-androgenic effects.Additionally, younger men, whose AGA symptoms are not yet more pronounced, may experience greater advantages from early intervention using it to potentially prevent AGA.Further research is recommended to fully comprehend these effects across different patient populations.In terms of safety, no side effects were reported on the topical application of C. aeruginosa in clinical trials [12,13], as opposed to those associated with finasteride and minoxidil, namely, sexual dysfunction and dermatological problems.This underscores the potential of C. aeruginosa as an AGA treatment, warranting further investigation.

Conclusions
In summary, this study combined network pharmacology and molecular docking to elucidate the active compounds, putative targets, and potential mechanisms of C. aeruginosa in the treatment of AGA.The results pinpointed that bioactive compounds in C. aeruginosa, such as trans-verbenol, myrtenal, carvone, alpha-atlantone, and isoaromandendrene epoxide, may play a crucial role in AGA by eliciting their effects on key target genes, including CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3.The molecular docking studies indicated that these bioactive components of C. aeruginosa could effectively act on these targets.Also, enrichment analyses revealed that C. aeruginosa may play its therapeutic role against AGA by modulating both HIF-1 and MAPK pathways, offering new approaches in the treatment and prevention of AGA.Substantially, the findings showed that C. aeruginosa could treat AGA via a mechanism involving multiple components, targets, and pathways.Hence, the valuable results may imply that C. aeruginosa could be a promising option in developing new drugs for AGA.As bound by the limitations of bioinformatics data and in silico network pharmacology and molecular docking analysis, however, experimental exploration and further confirmation via in vivo and in vitro studies are recommended to verify the findings of this study.

24 Figure 1 .
Figure 1.The 59 overlapping targets between C. aeruginosa and AGA identified by Venn diagram.

Figure 1 .
Figure 1.The 59 overlapping targets between C. aeruginosa and AGA identified by Venn diagram.

Biology 2024 , 24 Figure 2 .
Figure 2. Original PPI network of 59 potential targets of C. aeruginosa in AGA constructed by STRING.

Figure 2 .
Figure 2. Original PPI network of 59 potential targets of C. aeruginosa in AGA constructed by STRING.

Biology 2024 , 9 Figure 3 .
Figure 3.The PPI network (58 nodes and 449 edges) showing the degree of the targets reconstru by Cytoscape 3.10.2.The darker the color of the node, the greater its degree.
10.2 was u to analyze each node by incorporating three topological algorithms, namely, max clique centrality (MCC), maximum neighborhood component (MNC), and degree.Fi 4 shows the top 10 genes predicted by each algorithm based on their scores.Eight g (CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3) were screened out intersecting the three results, as revealed in Figure 4D.These highly connected gene shown in Figure 4E, represent the hub target genes of C. aeruginosa in AGA treatmen

Figure 3 .
Figure 3.The PPI network (58 nodes and 449 edges) showing the degree of the targets reconstructed by Cytoscape 3.10.2.The darker the color of the node, the greater its degree.

Figure 4 .
Figure 4.The top 10 hub gene networks of C. aeruginosa bioactive compounds against AGA from the employment of (A) maximal clique centrality, (B) maximum neighborhood component (MNC), and (C) degree.The warmer the color, the higher the score.The score correlates with the rank of genes in the network.(D) The Venn diagram intersecting the results of the three algorithms, revealing eight hub genes.(E) The PPI network of eight hub genes.Node color denotes interaction degree (red for high degree, orange for intermediate degree, and yellow for low degree).

Figure 4 .
Figure 4.The top 10 hub gene networks of C. aeruginosa bioactive compounds against AGA from the employment of (A) maximal clique centrality, (B) maximum neighborhood component (MNC), and (C) degree.The warmer the color, the higher the score.The score correlates with the rank of genes in the network.(D) The Venn diagram intersecting the results of the three algorithms, revealing eight hub genes.(E) The PPI network of eight hub genes.Node color denotes interaction degree (red for high degree, orange for intermediate degree, and yellow for low degree).

Figure 5 .
Figure 5.The modules obtained from the cluster analysis of the PPI network.

Figure 5 .
Figure 5.The modules obtained from the cluster analysis of the PPI network.

Biology 2024 , 24 Figure 6 .
Figure 6.Enrichment analyses of C. aeruginosa potential targets in AGA for the top 20 GO annotations and KEGG pathways: (A) GO biological processes, (B) GO cellular components, (C) GO molecular functions, and (D) KEGG pathways.

Figure 6 .
Figure 6.Enrichment analyses of C. aeruginosa potential targets in AGA for the top 20 GO annotations and KEGG pathways: (A) GO biological processes, (B) GO cellular components, (C) GO molecular functions, and (D) KEGG pathways.

Figure 7 .
Figure 7.The components-targets-pathways network displaying the potential mechanism of C. aeruginosa against AGA (yellow ellipses: compounds; red arrows: pathways; blue rectangles: targets).

Figure 7 .
Figure 7.The components-targets-pathways network displaying the potential mechanism of C. aeruginosa against AGA (yellow ellipses: compounds; red arrows: pathways; blue rectangles: targets).

Figure 8 .
Figure 8. Heatmap of the molecular docking of C. aeruginosa core compounds with hub target genes.The bluer the color, the greater the binding energy and binding affinity between the ligand and the receptor.

Figure 8 .
Figure 8. Heatmap of the molecular docking of C. aeruginosa core compounds with hub target genes.The bluer the color, the greater the binding energy and binding affinity between the ligand and the receptor.

Figure 8 .
Figure 8. Heatmap of the molecular docking of C. aeruginosa core compounds with hub target genes.The bluer the color, the greater the binding energy and binding affinity between the ligand and the receptor.

Figure 10 .
Figure 10.The potential mechanism of Curcuma aeruginosa Roxb.against androgenetic alopecia.Collectively, in the treatment of AGA, the MAPK pathway promotes hair follicle proliferation, differentiation, and self-renewal to maintain the hair cycle, and the HIF-1 pathway improves hair vascularization and nutrient supply conducive to hair growth.

Figure 10 .
Figure 10.The potential mechanism of Curcuma aeruginosa Roxb.against androgenetic alopecia.Collectively, in the treatment of AGA, the MAPK pathway promotes hair follicle proliferation, differentiation, and self-renewal to maintain the hair cycle, and the HIF-1 pathway improves hair vascularization and nutrient supply conducive to hair growth.
* Did not meet the screening conditions.

Table 2 .
Binding site interactions of top 4 ligand-protein complexes.